An incident happened. Is someone still scrubbing through days of footage by eye?
VCA is a video-analytics brain that attaches to the ordinary cameras you already have. Nothing is swapped out for AI cameras — we simply take the video you are already recording. It finds people and vehicles in your CCTV footage and organises them, so that later you can trace someone back from a single photo or a few conditions. Rewinding days of footage in sequence becomes narrowing candidates by combining conditions.
Request a Demo Check If It Works With Our CamerasThe cameras are already there. Yet when an incident happens, someone still sits down and plays it all back from the beginning.
Search works by combining filter conditions shown as chips — for example top: red plus bag: backpack — which produces a candidate list you can play back on the spot. It is not a system you can query in free-form speech, and we are equally plain about the last box in the diagram: we narrow the candidates, and your officer makes the final determination.
The first question in every first meeting is the same: do we have to replace all our cameras? The answer is always the same: no.
The biggest barrier to adopting security AI is the capital cost of replacing cameras. Remove that line item and the review stops being a hardware purchase and becomes a capability add-on — which is why decisions move faster.
Connects over ONVIF and RTSP. Camera brand does not matter, and there is no replacement cost.
We do not replace your VMS — the analytics sit on top of it, so day-to-day operation does not change.
Both on-premises and cloud deployments are supported. Organisations that cannot use cloud for policy reasons can still adopt it, and in an on-premises setup the data stays inside your environment.
Because the biggest barrier — the capital cost of replacing cameras — disappears, the budget line gets lighter and the decision moves faster.
We do not rely on faces alone — in the field, the face is more often the thing you do not have.
A 1:N search from a single photo, matched against many subjects. It answers the most basic request: find this person.
Finds the person by overall appearance even when no usable face was captured. This is the axis most used in the field.
Narrows by colour — a person in a red jacket, for instance. The more conditions you overlay, the fewer candidates remain.
Search by carried items, such as a person with a backpack. Clothing changes; the bag often does not.
Answers who this person moved together with. Once search extends into a relationship map, the job becomes investigative rather than mere retrieval.
Plots where the person passed through onto a map. The result reads as a city-scale trail rather than a single camera hit.
| Item | Specification |
|---|---|
| Camera Integration | ONVIF · RTSP (brand independent) |
| Minimum Image Quality | Ordinary 2MP CCTV |
| Search Types | Face · body · colour · belongings · companion network · movement trail |
| 1:N Search Response | Under one second |
| Face Database Size | 400M+ face database |
| Recognition Accuracy | 99.97% under KISA certification |
| Certifications | KISA · iBeta · GS Grade 1 · ISO |
| Deployment | On-premises · cloud |
| Existing VMS | Runs alongside, not replaced |
| Track Record | 20 deployments across 5 countries |
Telling you first what it does not do is usually more useful during evaluation.
Tracing a person or an object back after an incident: narrowing candidates by description, following the trail, checking who they moved with — missing-person searches are the classic case. Our place is sites where the cameras are already in place but there is no way to search them.
VCA is not a product that alerts you when something happens; it is a product that finds this person or this object. Real-time event detection — intrusion, fire, falls, theft, unusual behaviour, missing safety helmets — along with the retention and compression of footage, is handled by a separate product line — see AI BOX.
If you need the companion network and the movement trail as well, we are the right fit. What comes out is not one camera's hit but a picture stitched across a city.
Narrowing candidates is only the start. In the field, the next two questions are always the same — who did this person move with, and where did this person pass through. RedFace answers the first with a companion network; RedMap answers the second as a trail on a map. What comes out is not one camera's hit but a picture stitched across a city, which is why we are specialised in search and investigation rather than general analytics. On scale: there is a government city-wide deployment running at 1,000 channels, and our track record stands at 20 deployments across 5 countries.
See the site configuration that ties after-the-fact search and retention days into a single line.
The eight questions we receive most often during evaluation.
Products commonly evaluated alongside this one.
The retention-collapse diagram, specifications and FAQ
The terminal stays yours; only the authentication engine goes inside your server
1:N authentication, liveness and face indexing, delivered as an API
Send us your camera list and specifications and the name of the VMS you use, and we will check whether it applies and reply. That is a compatibility answer, not a replacement quotation.
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